With the proliferation of the Internet, as well as the growing popularity of mobile communication devices, marketplaces in which deals (e.g., offers) are exchanged (e.g., purchased and/or sold) have grown over time. This “deals marketplace” has grown quickly, but has encountered a number of challenges. For example, offers are usually poorly tailored to consumers (e.g., these offers are irrelevant or less relevant to consumers), which may lead many consumers to opt out of an option to receive such offers and/or a tendency of consumers to “tune out” or ignore offers that are received. Attempts to tailor offers to general interests (e.g., “sports” or “automotive”) may be too generic to generate a response from a consumer. Furthermore, recommendations of merchants to consumers based on generic interests or poorly tailored information results in the recommendations having lower creditability and being ignored or not valued. It would therefore be advantageous to have a system in which one or more merchants are able to accurately tailor relevant offers to one or more consumers. Likewise, it would be advantageous to have a system in which merchant recommendations are more accurately determined and provided to the consumers.